1. Field of the Invention
The present invention relates to an image processing apparatus which receives a color-image signal and converts the signal into color-image data for forming an image. In particular, the present invention relates to an image processing system performing a color-converting process, in which process lattice-point color-correction values not used in the color-converting process can be reduced and thus high accuracy can be achieved in the color-converting process. The lattice-point color-correction values are described later and a term `grid point` may be used instead of the above-mentioned term `lattice point`. Further, see an English article, A COLOR CORRECTION METHOD FROM STANDARDIZED COLOR-SPACE SIGNALS FOR PRINTERS, written by Manabu KOMATSU, Shogo OHNEDA, Hiroaki SUZUKI and Hiroki KUBOZONO of Ricoh Company Ltd., Japan (Oct. 5-III-p7), in ADVANCES IN NON-IMPACT PRINTING TECHNOLOGIES/JAPAN HARDCOPY +93, pages 545-548.
2. Related Art
A color-converting system in the related art obtains ink/toner quantity control values to form a color image using three colors, Y (yellow), M (magenta) and C (cyan), from color-image density signals indicating densities of three colors, R (red), G (green) and B (blue), using an interpolation method. According to a typical one of such a color-converting system, for example, as shown in FIG. 1, an input color-space extent, that is an input gamut is divided into identical three-dimensional figures such as triangle prisms. Previously calculated color correction values are assigned to each vertex of the three-dimensional figures (vertexes being referred to as lattice points, hereinafter) and color correction values of an input color-decomposed signal are calculated by linear-interpolating the color correction values assigned to the lattice points.
The input gamut is a color-space extent, within which extent input image data can represent colors and which extent is defined due to a capability of a relevant input device such as an image scanner supplying the input image data. An output gamut is a color-space extent, within which extent a relevant output device can reproduce colors and which extent is defined due to a capability of the output device such as a printer. With regard to the basic concept of the color space, see a Japanese book, IMAGE ENGINEERING, written by Toshi MINAMI and Osamu NAKAMURA, published by CORONA PUBLISHING CO., LTD., Tokyo, Japan, edited by Television Society, pages 19-22, `2.2.4 XYZ Color Representing System`. Further, see the above-mentioned English article, A COLOR CORRECTION METHOD FROM STANDARDIZED COLOR-SPACE SIGNALS FOR PRINTERS.
In such a color-converting system in the related art, interpolation accuracy improves as the input color-space divisions are made smaller, that is, a distance between each pair of the lattice points is made smaller. However, making the color-space divisions smaller results in an increase of a number of the lattice points. As a result, a capacity of a memory required to store the color correction values assigned to the lattice points is enlarged and time required to calculate the color correction values for the lattice points is enlarged. Further, hardware construction required for the calculation is made complicated. Further, a color-space color-reproduction extent of an image forming apparatus, that is, the output gamut does not actually have a simple shape such as a cube shown in FIG. 1 but has a complicated shape. Therefore, if it is attempted that color-space extent, that is, a gamut containing the complicated-shaped gamut of the image forming apparatus is evenly divided into small divisions as shown in FIG. 1, it may be necessary to assign many color correction values to lattice points located outside the output gamut.
Thus, in the related art, attempting the interpolation-accuracy improvement can result in many lattice-point color-correction values not actually being used for the color-conversion calculation. Therefore, hardware such as RAM required to load output-value information during the interpolation operation is complicated and time required for the interpolation operation is elongated.